The vast majority of people are poor multitaskers. To make matters worse, some of those who score worst on measures of multitasking performance tend to perceive that they are better at multitasking, with a negative correlation between perception and ability in large studies. These issues are particularly important, since in every day work-life, multitasking may often be necessary or efficient for a variety of human labor. Multitasking is directed to the cognitive process of concentrating on a specific sensory stimulus (i.e., attention to the stimulus).
A job may require an individual to direct attention to multiple tasks given the individual's responsibilities. For example, an individual may be required to view displays on several monitors and focus on certain information. However, the individual may neglect viewing one or more displays or areas on some displays and miss some information.
Interactions with partially autonomous processes are becoming an integral part of human industrial and civil function. Given semi-autonomy, many such tasks can often be monitored by a user at one time. In the course of operating a computer or vehicle, a single human might manage multiple processes, e.g., search and rescue type mobile robots, performing medical supply distribution, patient checkup, general cleanup, firefighting tasks, as well as process control with many dials or readings, security or surveillance monitoring, or other forms of human-based monitoring or tracking tasks. Generally, each automated agent or process only needs intermittent supervision and guidance from a human to optimize performance, and thus a single user can remotely operate or supervise multiple entities, for efficiency of labor. When controlling multiple automated processes at once, the user must decide how to distribute attention across each task. Even if the operator conducts the same type of task with each automated process, this form of human-system interaction requires a multitasking effort.
Unfortunately, most people are notoriously poor multitaskers and can remain unaware of visually subtle cues that indicate the need for user input. Further complicating the situation, individuals who perform worst at multitasking actually perceive they are better at multitasking, demonstrated by negative correlations between ability and perception of ability in large studies. To make matters worse, humans often naturally develop a plethora of biases of attention and perception. To address many of these issues, divided attention performance has been studied for many years. A further difficulty in multitasking is that brains rely heavily upon prediction and, fundamentally, are incapable of knowing what important information they have missed.
Eye tracking to ascertain point of gaze is a highly effective method of determining where people orient their attention, as well as what they deem important. Traditionally, eye tracking informed post-experiment analysis, rather than helping users in the field in real-time. For example, a study might analyze optimal gaze strategies in high-performing groups, and then at a later date, train new users on those previously discovered optimal search strategies. For example, studies have trained novice drivers' gaze to mimic experienced drivers with lower crash risk.
Alternatively, eye movement strategies can be employed to optimize real-time task performance, since many eye-movements are capable of being intentionally controlled. For those eye movements that cannot easily be intentionally controlled, salient “pop-out” cues (e.g., flashing red box around target) can reliably direct attention in a more automatic, bottom-up manner. As we discuss further, many eye tracking systems have been developed for real-time control, with very few attempting pure assistance, though none were both successful and domain-general. Hence there is a need for such an assistive system.
Tracking a participant's eye movements while multitasking is an especially good way to glean optimal cognitive strategies. Much work has shown that eye tracking to determine point of gaze can reliably convey the location at which humans' visual attention is currently directed. Locus of attention is a factor that can illustrate which of multiple tasks a participant is currently attending to, as well as many other details. Further, measuring where humans look tends to be highly informative of what is interesting to them in a particular scene, and can be helpful for inferring cognitive strategies. Generally, gaze appears deeply intertwined with cognitive processes.
Multitasking principles also apply when managing multiple items in working memory. For working memory, another cognitive construct that is difficult to measure and discussed at length below, eye movement paradigms have revealed how visual search tasks can be interfered with when working memory is being taxed.
Though many paradigms have been developed to study multitasking using eye tracking, most traditional applications of eye tracking are not used in real time, but instead to augment training, or simply to observe optimal strategies. For an example of training, post-experiment analysis of gaze data can be used to determine an attention strategy of the best-performing participants or groups. Then, these higher-performing strategies can be taught during training sessions at a later date. Implemented examples include educating health care professionals on visual scanning patterns associated with reduced incidence of medical documentation errors, and training novice drivers' gaze behaviors to mimic more experienced drivers with lower crash risk. As eye tracking methods become more popular, they have been applied in the field of human-computer interaction and usability, as well as human-robot interaction, though in this area, guiding principles for optimal gaze strategies are still nascent.
Real-time reminders for tasks can improve user performance. Generally, real-time cuing of goals can speed or increase the accuracy of detection. Highlighting display elements in a multi-display may assist in directing attention, though eye tracking may often be critical to reliably automate such reminders for many tasks. As described above, there is little previous work developing real-time eye tracking assistance, with most research focused on training, evaluation, or basic hypothesis testing. The real-time systems developed previously are lacking in domain-generality, utility, and flexibility. There is a need for an assistive system and methods for managing multiple visual tasks, which is domain-general, transparent, intuitive, non-interfering, non-command, improves control (without replacing direct control), and adaptively extrapolates to a variety of circumstances.
Visual attention of the individual may be inferred from measuring the location of an individual's gaze on a display, for example, a graphical user interface on a monitor. Various technologies exist for measuring the location of an individual's gaze and attention. A mouse cursor location may be used as an implicit measurement of attention. For example, a software program may be operated to identify the location of a digital cursor on a graphical user interface positioned by a mouse and by implication an individual's gaze. Also, an optical sensor may measure the location or duration of an individual's gaze. For example, a software program may calculate a vector between a pupil center and a corneal reflection to determine the location of an individual's gaze.
Eye-tracking systems measure the location of an individual's gaze on a display to determine whether the individual's visual attention is directed on a certain area. Some conventional eye-tracking systems determine whether the individual's visual attention is directed to specific content in a certain area on the display. Hence these systems are dependent on the content displayed on the screen. Other eye-tracking systems only provide a visual cue, such as show a “warning”, to direct an individual's visual attention. There is a need for a system and methods to provide a cue to direct visual attention to an area independent of the content conveyed on the screen display.
The invention solves the above recognized needs by providing a system and methods for providing sensory cue to direct visual attention to an area neglected by an individual's gaze.